Digital assistant

ABSTRACT

One or more computing devices, systems, and/or methods for dynamically selecting a personality for a digital assistant are provided. For example, audio associated with a conversation with a digital assistant may be received from a user. The audio may be converted into a request comprising text. A task may be determined based upon the request. One or more sentences associated with information associated with the task may be determined. A context of the conversation may be determined based upon the request and a user profile of the user. A first personality may be selected for the digital assistant from one or more personalities based upon the context of the conversation. The first personality may be used to generate audio of the one or more sentences. The audio of the one or more sentences may be presented as part of the conversation to the user.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to and is a continuation of U.S.application Ser. No. 15/396,555, filed on Dec. 31, 2016, entitled“DIGITAL ASSISTANT”, which is incorporated herein.

BACKGROUND

Many services, such as websites, apps, social networks, etc., may employvarious techniques to help a user to perform a task. For example, awebsite may display a form with various input fields that eachcorrespond to data that may be input by the user. The user may submitthe data via the form, and the website (e.g., and/or an entity withaccess to the website) may use the data submitted via the form toperform the task.

In an example, properly performing the task may require more than onetype of information from the user. For example, to reserve a hotel roomwith a waterfront view, it may be necessary to first receive selection,by the user, of a hotel that has waterfront views available. The use ofa single form with various input fields may thus be inconvenient,insufficient and/or inefficient. For example, the form may requirevisual attention from the user, which the user may be unable to providewhile driving. Thus, the user may be unable to reserve the hotel untilthe user reaches a destination and ceases driving.

SUMMARY

In accordance with the present disclosure, one or more computing devicesand/or methods for dynamically selecting a personality for a digitalassistant are provided. In an example, audio associated with aconversation with a digital assistant (e.g., on a mobile device) may bereceived from a user (e.g., via a microphone). The audio may beconverted into a request comprising text (e.g., using speechrecognition). A task (e.g., that the user may intend to perform) (e.g.,make a reservation) may be determined (e.g., identified) based upon therequest. One or more sentences (e.g., questions, suggestions, trivia,etc.) associated with information (e.g., name, location, dates, etc.)associated with (e.g., used to perform) the task may be determined. Acontext of the conversation may be determined based upon the request(e.g., to make the reservation) and a user profile of the user (e.g.,comprising locations of the user, history of the user, etc.). A firstpersonality may be selected for the digital assistant from one or morepersonalities (e.g., actors, athletes, celebrities, etc.) based upon thecontext of the conversation. The first personality may be used togenerate audio of the one or more sentences. The audio of the one ormore sentences may be presented (e.g., played) as part of theconversation (e.g., via a speaker) to the user.

DESCRIPTION OF THE DRAWINGS

While the techniques presented herein may be embodied in alternativeforms, the particular embodiments illustrated in the drawings are only afew examples that are supplemental of the description provided herein.These embodiments are not to be interpreted in a limiting manner, suchas limiting the claims appended hereto.

FIG. 1 is an illustration of a scenario involving various examples ofnetworks that may connect servers and clients.

FIG. 2 is an illustration of a scenario involving an exampleconfiguration of a server that may utilize and/or implement at least aportion of the techniques presented herein.

FIG. 3 is an illustration of a scenario involving an exampleconfiguration of a client that may utilize and/or implement at least aportion of the techniques presented herein.

FIG. 4 is a flow chart illustrating an example method for dynamicallyselecting a personality for a digital assistant.

FIG. 5A is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where auser is making a request.

FIG. 5B is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where atask is determined.

FIG. 5C is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where oneor more sentences associated with information required to perform a taskare determined.

FIG. 5D is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where thepersonality is selected.

FIG. 5E is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where oneor more sentences are presented to a user using the personality.

FIG. 5F is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where auser is responding to one or more sentences.

FIG. 5G is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where atask is performed.

FIG. 5H is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant, where auser is notified of performance of a task.

FIG. 5I is a component block diagram illustrating an example system fordynamically selecting a personality for a digital assistant.

FIG. 6 is an illustration of a scenario featuring an examplenon-transitory machine readable medium in accordance with one or more ofthe provisions set forth herein.

DETAILED DESCRIPTION

Subject matter will now be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, specific example embodiments. Thisdescription is not intended as an extensive or detailed discussion ofknown concepts. Details that are known generally to those of ordinaryskill in the relevant art may have been omitted, or may be handled insummary fashion.

The following subject matter may be embodied in a variety of differentforms, such as methods, devices, components, and/or systems.Accordingly, this subject matter is not intended to be construed aslimited to any example embodiments set forth herein. Rather, exampleembodiments are provided merely to be illustrative. Such embodimentsmay, for example, take the form of hardware, software, firmware or anycombination thereof.

1. Computing Scenario

The following provides a discussion of some types of computing scenariosin which the disclosed subject matter may be utilized and/orimplemented.

1.1. Networking

FIG. 1 is an interaction diagram of a scenario 100 illustrating aservice 102 provided by a set of servers 104 to a set of client devices110 via various types of networks. The servers 104 and/or client devices110 may be capable of transmitting, receiving, processing, and/orstoring many types of signals, such as in memory as physical memorystates.

The servers 104 of the service 102 may be internally connected via alocal area network 106 (LAN), such as a wired network where networkadapters on the respective servers 104 are interconnected via cables(e.g., coaxial and/or fiber optic cabling), and may be connected invarious topologies (e.g., buses, token rings, meshes, and/or trees). Theservers 104 may be interconnected directly, or through one or more othernetworking devices, such as routers, switches, and/or repeaters. Theservers 104 may utilize a variety of physical networking protocols(e.g., Ethernet and/or Fiber Channel) and/or logical networkingprotocols (e.g., variants of an Internet Protocol (IP), a TransmissionControl Protocol (TCP), and/or a User Datagram Protocol (UDP). The localarea network 106 may include, e.g., analog telephone lines, such as atwisted wire pair, a coaxial cable, full or fractional digital linesincluding T1, T2, T3, or T4 type lines, Integrated Services DigitalNetworks (ISDNs), Digital Subscriber Lines (DSLs), wireless linksincluding satellite links, or other communication links or channels,such as may be known to those skilled in the art. The local area network106 may be organized according to one or more network architectures,such as server/client, peer-to-peer, and/or mesh architectures, and/or avariety of roles, such as administrative servers, authenticationservers, security monitor servers, data stores for objects such as filesand databases, business logic servers, time synchronization servers,and/or front-end servers providing a user-facing interface for theservice 102.

Likewise, the local area network 106 may comprise one or moresub-networks, such as may employ differing architectures, may becompliant or compatible with differing protocols and/or may interoperatewithin the local area network 106. Additionally, a variety of local areanetworks 106 may be interconnected; e.g., a router may provide a linkbetween otherwise separate and independent local area networks 106.

In the scenario 100 of FIG. 1, the local area network 106 of the service102 is connected to a wide area network 108 (WAN) that allows theservice 102 to exchange data with other services 102 and/or clientdevices 110. The wide area network 108 may encompass variouscombinations of devices with varying levels of distribution andexposure, such as a public wide-area network (e.g., the Internet) and/ora private network (e.g., a virtual private network (VPN) of adistributed enterprise).

In the scenario 100 of FIG. 1, the service 102 may be accessed via thewide area network 108 by a user 112 of one or more client devices 110,such as a portable media player (e.g., an electronic text reader, anaudio device, or a portable gaming, exercise, or navigation device); aportable communication device (e.g., a camera, a phone, a wearable or atext chatting device); a workstation; and/or a laptop form factorcomputer. The respective client devices 110 may communicate with theservice 102 via various connections to the wide area network 108. As afirst such example, one or more client devices 110 may comprise acellular communicator and may communicate with the service 102 byconnecting to the wide area network 108 via a wireless local areanetwork 106 provided by a cellular provider. As a second such example,one or more client devices 110 may communicate with the service 102 byconnecting to the wide area network 108 via a wireless local areanetwork 106 provided by a location such as the user's home or workplace(e.g., a WiFi (Institute of Electrical and Electronics Engineers (IEEE)Standard 802.11) network or a Bluetooth (IEEE Standard 802.15.1)personal area network). In this manner, the servers 104 and the clientdevices 110 may communicate over various types of networks. Other typesof networks that may be accessed by the servers 104 and/or clientdevices 110 include mass storage, such as network attached storage(NAS), a storage area network (SAN), or other forms of computer ormachine readable media.

1.2. Server Configuration

FIG. 2 presents a schematic architecture diagram 200 of a server 104that may utilize at least a portion of the techniques provided herein.Such a server 104 may vary widely in configuration or capabilities,alone or in conjunction with other servers, in order to provide aservice such as the service 102.

The server 104 may comprise one or more processors 210 that processinstructions. The one or more processors 210 may optionally include aplurality of cores; one or more coprocessors, such as a mathematicscoprocessor or an integrated graphical processing unit (GPU); and/or oneor more layers of local cache memory. The server 104 may comprise memory202 storing various forms of applications, such as an operating system204; one or more server applications 206, such as a hypertext transportprotocol (HTTP) server, a file transfer protocol (FTP) server, or asimple mail transport protocol (SMTP) server; and/or various forms ofdata, such as a database 208 or a file system. The server 104 maycomprise a variety of peripheral components, such as a wired and/orwireless network adapter 214 connectible to a local area network and/orwide area network; one or more storage components 216, such as a harddisk drive, a solid-state storage device (SSD), a flash memory device,and/or a magnetic and/or optical disk reader.

The server 104 may comprise a mainboard featuring one or morecommunication buses 212 that interconnect the processor 210, the memory202, and various peripherals, using a variety of bus technologies, suchas a variant of a serial or parallel AT Attachment (ATA) bus protocol; aUniform Serial Bus (USB) protocol; and/or Small Computer SystemInterface (SCI) bus protocol. In a multibus scenario, a communicationbus 212 may interconnect the server 104 with at least one other server.Other components that may optionally be included with the server 104(though not shown in the schematic diagram 200 of FIG. 2) include adisplay; a display adapter, such as a graphical processing unit (GPU);input peripherals, such as a keyboard and/or mouse; and a flash memorydevice that may store a basic input/output system (BIOS) routine thatfacilitates booting the server 104 to a state of readiness.

The server 104 may operate in various physical enclosures, such as adesktop or tower, and/or may be integrated with a display as an“all-in-one” device. The server 104 may be mounted horizontally and/orin a cabinet or rack, and/or may simply comprise an interconnected setof components. The server 104 may comprise a dedicated and/or sharedpower supply 218 that supplies and/or regulates power for the othercomponents. The server 104 may provide power to and/or receive powerfrom another server and/or other devices. The server 104 may comprise ashared and/or dedicated climate control unit 220 that regulates climateproperties, such as temperature, humidity, and/or airflow. Many suchservers 104 may be configured and/or adapted to utilize at least aportion of the techniques presented herein.

1.3. Client Device Configuration

FIG. 3 presents a schematic architecture diagram 300 of a client device110 whereupon at least a portion of the techniques presented herein maybe implemented. Such a client device 110 may vary widely inconfiguration or capabilities, in order to provide a variety offunctionality to a user such as the user 112. The client device 110 maybe provided in a variety of form factors, such as a desktop or towerworkstation; an “all-in-one” device integrated with a display 308; alaptop, tablet, convertible tablet, or palmtop device; a wearable devicemountable in a headset, eyeglass, earpiece, and/or wristwatch, and/orintegrated with an article of clothing; and/or a component of a piece offurniture, such as a tabletop, and/or of another device, such as avehicle or residence. The client device 110 may serve the user in avariety of roles, such as a workstation, kiosk, media player, gamingdevice, and/or appliance.

The client device 110 may comprise one or more processors 310 thatprocess instructions. The one or more processors 310 may optionallyinclude a plurality of cores; one or more coprocessors, such as amathematics coprocessor or an integrated graphical processing unit(GPU); and/or one or more layers of local cache memory. The clientdevice 110 may comprise memory 301 storing various forms ofapplications, such as an operating system 303; one or more userapplications 302, such as document applications, media applications,file and/or data access applications, communication applications such asweb browsers and/or email clients, utilities, and/or games; and/ordrivers for various peripherals. The client device 110 may comprise avariety of peripheral components, such as a wired and/or wirelessnetwork adapter 306 connectible to a local area network and/or wide areanetwork; one or more output components, such as a display 308 coupledwith a display adapter (optionally including a graphical processing unit(GPU)), a sound adapter coupled with a speaker, and/or a printer; inputdevices for receiving input from the user, such as a keyboard 311, amouse, a microphone, a camera, and/or a touch-sensitive component of thedisplay 308; and/or environmental sensors, such as a global positioningsystem (GPS) receiver 319 that detects the location, velocity, and/oracceleration of the client device 110, a compass, accelerometer, and/orgyroscope that detects a physical orientation of the client device 110.Other components that may optionally be included with the client device110 (though not shown in the schematic architecture diagram 300 of FIG.3) include one or more storage components, such as a hard disk drive, asolid-state storage device (SSD), a flash memory device, and/or amagnetic and/or optical disk reader; and/or a flash memory device thatmay store a basic input/output system (BIOS) routine that facilitatesbooting the client device 110 to a state of readiness; and a climatecontrol unit that regulates climate properties, such as temperature,humidity, and airflow.

The client device 110 may comprise a mainboard featuring one or morecommunication buses 312 that interconnect the processor 310, the memory301, and various peripherals, using a variety of bus technologies, suchas a variant of a serial or parallel AT Attachment (ATA) bus protocol;the Uniform Serial Bus (USB) protocol; and/or the Small Computer SystemInterface (SCI) bus protocol. The client device 110 may comprise adedicated and/or shared power supply 318 that supplies and/or regulatespower for other components, and/or a battery 304 that stores power foruse while the client device 110 is not connected to a power source viathe power supply 318. The client device 110 may provide power to and/orreceive power from other client devices.

In some scenarios, as a user 112 interacts with a software applicationon a client device 110 (e.g., an instant messenger and/or electronicmail application), descriptive content in the form of signals or storedphysical states within memory (e.g., an email address, instant messengeridentifier, phone number, postal address, message content, date, and/ortime) may be identified. Descriptive content may be stored, typicallyalong with contextual content. For example, the source of a phone number(e.g., a communication received from another user via an instantmessenger application) may be stored as contextual content associatedwith the phone number. Contextual content, therefore, may identifycircumstances surrounding receipt of a phone number (e.g., the date ortime that the phone number was received), and may be associated withdescriptive content. Contextual content, may, for example, be used tosubsequently search for associated descriptive content. For example, asearch for phone numbers received from specific individuals, receivedvia an instant messenger application or at a given date or time, may beinitiated. The client device 110 may include one or more servers thatmay locally serve the client device 110 and/or other client devices ofthe user 112 and/or other individuals. For example, a locally installedwebserver may provide web content in response to locally submitted webrequests. Many such client devices 110 may be configured and/or adaptedto utilize at least a portion of the techniques presented herein.

2. Presented Techniques

One or more computing devices and/or techniques for dynamicallyselecting a personality for a digital assistant are provided. Forexample, a user may want to perform a task, such as make a reservation(e.g., at a hotel, restaurant, etc.). Performance of the task may useand/or require one or more pieces of information, and thus may consume asignificant amount of attention, time and/or resources of the user(e.g., to find an appropriate entity, to contact the entity, tocommunicate a desire of the user to the entity, to provide informationused to perform the task to the entity, etc.). A (e.g., voice-based)digital assistant may be used to assist the user in performing the task.The digital assistant may have a single voice that communicates with theuser, irrespective of what task the user wants to perform. For example,the single voice may be used when the user wants to perform a first taskassociated with sports and when the user wants to perform a second taskassociated with science. The single voice may be monotonous,uninteresting and/or tiring for the user, and as a result, the user mayavoid using the digital assistant in situations where such use would beuseful and save time, resources, etc. Thus, in accordance with one ormore of the techniques presented herein, a personality may dynamicallybe selected for the digital assistant to encourage the user to performthe task in a manner that is efficient, convenient, low cost and/ortimely. Similarly, as provided herein, a service that works with amessaging interface may be used to assist the user in dynamicallyselecting the personality and/or to perform the task.

An embodiment of dynamically selecting a personality for a digitalassistant is illustrated by an example method 400 of FIG. 4. A user,such as user Jill, may access and/or interact with a digital assistant(e.g., and/or another service). The digital assistant may be accessedand/or interacted with via one or more interfaces on a device of theuser, such as a microphone and/or a messaging (e.g., chat, textmessaging, etc.) interface of a mobile device. The user may interactwith the digital assistant by providing one or more voice commands intothe microphone. In an example, the user may interact with the digitalassistant by typing a message into the messaging interface. Accordingly,at 404, audio may be received (e.g., by the digital assistant) from theuser (e.g., such as voice, by the user, etc.). The audio may beassociated with (e.g., a part of) a conversation (e.g., of the user)with the digital assistant. The audio may be received via the microphoneof the device. At 406, the audio may be converted into a requestcomprising text. The converting may be performed using one or morespeech recognition techniques. In an example, the request may compriseone or more sentences in a first language, such as English. The requestmay, for example, be made as a part of a chat conversation or a textmessaging conversation (e.g., with the digital assistant, with anotheruser, etc.), etc. At 408, a task (e.g., that the user may intend toperform) may be determined (e.g., identified) based upon the request. Inan example, the one or more sentences may be analyzed and/or scanned forkeywords to determine a likely objective of the user (e.g., usingnatural language processing, word/phrase matching, etc.).

At 410, one or more sentences (e.g., questions) that are associated with(e.g., information associated with (e.g., required to perform)) the taskmay be determined (e.g., using a finite-state machine (FSM) associatedwith the task). For example, a determination may be made that certaininformation is needed and/or may be useful to perform the task. The oneor more sentences may be designed to request and/or obtain theinformation from the user. For example, if an exemplary task requires aname and age of the user to be properly performed, a first exemplaryquestion inquiring about the name of the user (e.g., “What is yourname?”) and a second exemplary question inquiring about the age of theuser (e.g., “What is your age?”) may be determined.

At 412, a context of the conversation may be determined based upon therequest and/or a user profile of the user. The user profile may compriseand/or be created using information associated with the user such as(e.g., current, past, visited, home, office, shopping, etc.) locationsof the user (e.g., determined using a GPS unit of the device), a historyof communications associated with the user (e.g., chat, email, textmessages, phone calls, etc.), a calendar of the user, a search historyof the user, a browsing history of the user, etc. For example, one ormore purchases (e.g., of books, movies, tickets, products, services,etc.) of the user may be determined by scanning the communicationsassociated with the user, and stored in the user profile. In anotherexample, one or more frequent destinations of the user may be determinedby scanning the past locations of the user, and stored in the userprofile. In another example, one or more interests (e.g., sports, food,finance, education, science, technology, languages, woodworking, etc.)of the user may be determined based upon the information associated withthe user, and stored in the user profile. In another example, travelplans (e.g., a future destination) of the user may be predicted basedupon (e.g., purchased tickets identified in) the information associatedwith the user, and stored in the user profile. The context of theconversation may be determined by identifying one or more portions ofthe user profile relevant to the request and/or the task.

At 414, a first personality may be selected from a plurality ofpersonalities based upon the context of the conversation. The pluralityof personalities may be stored in a database of personalities. Thedatabase of personalities may be stored on the device or on a serveraccessed by the device via a network connection. In an example, thedatabase of personalities may be dynamically updated to improve one ormore personalities or to introduce one or more new personalities (e.g.,based upon the information associated with the user, based upon a trendamong a plurality of users, in response to a request by one or moreusers, etc.). The personalities may each correspond to a celebrity, anathlete, a character (e.g., from a movie, show, cartoon, etc.), anactor, a political figure, or a historical figure. For example, thefirst personality may correspond to a first political figure, while asecond personality may correspond to a first athlete. In an example, thefirst personality may be selected over the second personality inresponse to determining that the context of the conversation isassociated with politics, and/or that the first political figure islikely to be of more interest to the user than the first athlete. In thedatabase, the first personality may be stored in association with afirst topic, while the second personality may be stored in associationwith a second topic (e.g., different than the first topic).

It may be appreciated that a personality may comprise one or moredimensions (e.g., in combination) associated with an entity (e.g., anindividual). A first dimension of the personality may be a voice of theentity, a second dimension of the personality may be a tone of theentity, a third dimension of the personality may be manners of theentity, a fourth dimension of the personality may be a style of theentity, a fifth dimension of the personality may be preferred words andphrases of the entity, etc.

It may further be appreciated that a model of a personality may be builtby mining one or more databases (e.g., to determine one or moredimensions of the personality), such as social media of an individualcorresponding to the personality, news articles, interviews (e.g., text,audio and/or video), scripts (e.g., of a movie or TV show correspondingto the personality). Alternatively and/or additionally, the individualcorresponding to the personality may be interviewed to obtain audio ofthe individual pronouncing one or more desired words, and the model ofthe personality may be built and/or supplemented using the audio fromthe interview.

In an example, a first degree of relevance of the first personality tothe context of the conversation may be calculated, and a second degreeof relevance of a second personality of the plurality of personalitiesto the context of the conversation may be calculated. The degrees ofrelevance may be based upon topical relevance of the respectivepersonalities to the context and/or user relevance, for example.Timeliness, authority and/or novelty may also factor into determiningthe degrees of relevance. If a determination is made that the firstdegree of relevance is greater than the second degree of relevance, thefirst personality is selected. If instead, a determination is made thatthe second degree of relevance is greater than the first degree ofrelevance, the second personality is selected. In an example, the firstpersonality may correspond to a voice of a first person and the secondpersonality may correspond to a voice of a second person different thanthe first person.

At 416, audio of the one or more sentences may be generated using thefirst personality. For example, the digital assistant may be configuredto operate, process input and/or provide output while adopting the firstpersonality of the first political figure. For example, the one or moresentences may be customized to incorporate preferred words and phrasesof the first political figure, and audio resembling the voice of thefirst political figure speaking in the tone of the first politicalfigure may be generated.

At 418, the audio of the one or more sentences may be presented as partof the conversation to the user. For example, the audio may be outputvia a speaker. It may be appreciated that the audio of the one or moresentences may be a response to the audio received from the user, andthat the user may thus feel as though the user is conversing with (e.g.,and/or being guided by) the first political figure rather than thedevice.

In some examples, the audio is presented in response to determining thatthe user prefers that the conversation be continued in an audio formatof a plurality of formats of communication stored in a second databasethan in one or more other formats (e.g., text, email, video, etc.) ofthe plurality of formats of communication.

In one example of determining the one or more sentences, a plurality ofsentences comprising the one or more sentences may be ranked. It may beappreciated that the plurality of sentences may be ranked based uponpast requests and/or actions by the user and/or other informationassociated with (e.g., received from) the user, past requests and/oractions by users other than the user and/or other information associatedwith (e.g., received from) users other than the user, and/or based uponother information, such as default settings, local, regional and/orglobal settings, etc. A determination may be made that the one or moresentences are ranked above a threshold (e.g., but that one or more othersentences in the plurality of sentences are not ranked above thethreshold). The one or more sentences may thus be selected forpresentation based upon the determination that the one or more sentencesare ranked above the threshold (e.g., but the one or more othersentences in the plurality of sentences may not be selected forpresentation based upon the determination that they are not ranked abovethe threshold). For example, the top X (e.g., 1, 2, 3, 4 . . . ) rankedsentences may be selected for presentation. It may be appreciated thatthe selection of the one or more sentences may be reflective of adetermination that the user is likely to respond to the one or moresentences.

In some examples, a plurality of personalities may be selected for thedigital assistant based upon the context of the conversation, inresponse to a (single) request. For example, the first personality and athird personality may be concurrently used and/or may be alternated inthe conversation if a determination is made that both personalities arerelevant to the context and/or share a common background. For example,the first personality may correspond to a first character and the thirdpersonality may correspond to a second character that featured in a samestory, movie, show, etc. as the first character.

In some examples, audio associated with a response to the audio of theone or more sentences may be received (e.g., via the microphone) fromthe user. The audio may be converted into a response comprising text.The task may be performed based upon the response. For example, for anexemplary task of making a reservation, where a first exemplary answerchoice comprising the name John is received, the reservation may be made(e.g., by contacting the service and/or one or more other services,servers, etc.) in the name of John. It may be appreciated thatconfirmation and/or information associated with the performance of thetask may be provided to the user.

In some examples, after 418, second audio (e.g., speech comprising “whowas Elvis”) may be received from the user via the microphone inassociation with the (e.g., same) conversation with the digitalassistant. Speech recognition may be used to convert the second audiointo a second request comprising text (e.g., different than therequest). A second task (e.g., a request for information about Elvis)may be determined based upon the second request. One or more secondsentences (e.g., “Elvis was an American musical icon”) associated withthe second task may be determined, and a second context of theconversation may be determined based upon the second request and theuser profile of the user (e.g., indicating that the user is an avidmusic fan). A second personality (e.g., of a musician, or known musicalcommentator) may be selected for the digital assistant from theplurality of personalities based upon the second context of theconversation. Audio of the one or more second sentences may be generatedusing the second personality and presented to the user (e.g., via thespeaker).

In some examples, a first agent may be selected from a plurality of theagents (e.g., stored in a database) based upon the task. The first agentmay be configured to perform at least some of the task (e.g., reserve ahotel), while a second agent of the plurality of the agents may beconfigured to perform one or more other tasks (e.g., reserve arestaurant). For example, a first degree of relevance of the first agentto the task may be calculated, and a second degree of relevance of thesecond agent of the plurality of agents to the task may be calculated.If a determination is made that the first degree of relevance is greaterthan the second degree of relevance, the first agent may be selected.Instructions to perform the task may be provided via the first agent.Confirmation that the task has been performed via the first agent may bereceived, and audio indicative of the confirmation as part of theconversation may be presented to the user (e.g., via the speaker).

In some examples, after the audio is presented, feedback associated withthe conversation may be received (e.g., from the user). For example, thefeedback may comprise speech saying “what a great guy” or “I hate thatguy.” Alternatively and/or additionally, a tone associated with approvalor disapproval may be detected in the feedback. Based upon the feedback,the first personality may be raised or lowered in a ranking ofpersonalities and/or an indication of a like or dislike of the firstpersonality may be stored in user profile.

It may be appreciated that audio is one example of a format that can beused in the conversation. Examples that incorporate (e.g., merely oradditionally) text, or video, are also contemplated. For example, thefirst personality may include a first video (e.g., of an actual person,an animation, etc.) of a character, and in the video, lips of thecharacter may be dynamically displayed in a manner that matches speechin audio expressed by the character in the conversation.

FIGS. 5A-5I illustrate examples of a system 501 for dynamicallyselecting a personality for a digital assistant. FIG. 5A illustrates adevice 500 of the user displaying a digital assistant interface. Thedevice 500 may comprise a button 502, a microphone 506 and a speaker508. The digital assistant interface may comprise an area 504 fordisplay of a conversation between the user and a second user (e.g., thedigital assistant). Audio 510 comprising speech may be received (e.g.,from the user) via the microphone 506 and converted into a request 512comprising text, which may be displayed in the area 504. For example,the audio 510 may comprise the user saying “I'd like to reserve a tableat a restaurant for me and my friends,” and speech recognition may beused to generate the request 512.

FIG. 5B illustrates a backend system 550 (e.g., on the device 500 of theuser, on a server connected to the device via a network, etc.) that mayreceive and/or classify the request 512 from the user as an inputmessage 514. A task 516 (e.g., that the user may intend to perform) maybe determined (e.g., identified, predicted, selected, etc.) based uponthe request 512. For example, the backend system 550 may access adatabase comprising a plurality of tasks (e.g., and one or morekeywords, terms, types and/or formats of information, metadata, etc.associated with each task), and may select the task 516 “reserve tableat restaurant” from the plurality of tasks (e.g., upon determining thatthe task 516, compared to the remaining tasks of the plurality of tasks,is the most likely to be desired to be performed by the user based uponan analysis of the request 512). It may be appreciated that supplementalinformation associated with the task 516, such as location, date, etc.,may also be determined based upon the request 512. For example, thepresence of the words “reserve” and “restaurant” in the request 512 maybe used to determine that the user would like to make a reservation at arestaurant, while the presence of the words “me and my friends” may beused to determine an estimate of a number of people (e.g., three ormore) associated with performance of the task 516, and the absence of adate may be used to predict that the task is associated with a currentday.

FIG. 5C illustrates the backend system 550 receiving and/or classifyingthe task 516 from the user as an input 518 and using the input 518determined based upon the request 512 to determine one or more sentences(e.g., questions, statements, etc.) associated with (e.g., informationrequired to perform) the task 518. For example, the backend system 550may access a database comprising a plurality of sentences (e.g., and oneor more keywords, terms, types and/or formats of information, metadata,etc. associated with each sentence), and may select first sentence 520“What type of restaurant?” and/or second sentence 522 “How many friendsare joining you” from the plurality of sentences (e.g., upon determiningthat the first sentence 520 and/or the second sentence 522, compared tothe remaining sentences of the plurality of sentences, are the mostlikely to be associated with information needed and/or useful inperforming the input 518).

FIG. 5D illustrates the backend system 550 receiving and/or classifyingthe task 516 from the user as an input 524, receiving and/or classifyinginformation from a user profile of the user as input 526, and using theinput 524 determined based upon the task 516 and/or the input 526 fromthe user profile to determine one or more personalities (e.g.,characters, actors, athletes, coaches, politicians, etc.) associatedwith (e.g., sharing a common genre, theme, topic, era, etc.) the input524 and/or the input 526 of the user profile. For example, the backendsystem 550 may access a database comprising a plurality of personalities(e.g., and one or more keywords, terms, types and/or formats ofinformation, metadata, etc. associated with each personality), and mayselect first personality 528 “Host of Food TV Show” from the pluralityof personalities (e.g., upon determining that the first personality 528,compared to the remaining personalities of the plurality ofpersonalities, is the most likely to be of interest to the user basedupon the input 524 and the input 526). This selection may be based upona previous purchase, by the user, of a season of a food-related TV showbeing identified in the user profile (e.g., after being extracted from aTV browsing history, an email account and/or another messaging accountof the user). The user profile may also comprise an indication of acurrent location of the user, which may be determined based upon a GPS(e.g., or other location identification mechanism) component of thedevice. A determination that the current location is changing fasterthan a threshold rate may be used to determine whether the user isdriving (e.g., or otherwise traveling in a motor vehicle), walking,stationary, etc., which may be used to select the first personality 528and/or for making one or more other determinations disclosed herein.

FIG. 5E illustrates (e.g., versions of) the first sentence 520 and thesecond sentence 522 of the one or more sentences associated with thetask 516 being provided (e.g., via the digital assistant interface) astext 530 and/or as speech output as audio 532 via the speakers 508 ofthe device 500. For example, the text 530 and/or the audio 532 mayexpress the sentences “What type of restaurant were you thinking oftrying Joe?” and “And how many of your friends are joining you?”. Thefirst sentence 520 and/or the second sentence 520 may be modified and/orcustomized based upon the first personality 528 selected in FIG. 5D. Forexample, the first sentence 520 and/or the second sentence 522 may becustomized to be pronounced with a regional accent associated with thefirst personality 528, and/or to include key words or phrases associatedwith the first personality 528 (e.g., and/or to exclude key words,phrases, etc. not associated or negatively associated with the firstpersonality 528). In another example, the first sentence 520 and/or thesecond sentence 522 may be customized to be long winded, concise,polite, blunt, etc. depending upon the first personality 528.

FIG. 5F illustrates the receipt of a response to the first sentence 520and/or the second sentence 522 (e.g., comprising “There's 5 of them, andwe're craving some Mexican food”) from the user (e.g., via themicrophone 506). The response may be audio 534 comprising speech by theuser, which may be converted into text 536 using speech recognition.

FIG. 5G illustrates the backend system 550 using the response (e.g., andone or more other indications associated with the request 512, the task516, the user profile, etc.) to perform the task 516. For example, thebackend system 550 may identify 538 a provider suitable for the task516, submit 540 information determined based upon the request 512, suchas an indication of the desire to reserve a table at a restaurant, andinformation determined based upon the response by the user, such as anindication of the desire for the restaurant to be a Mexican restaurantand to seat 6 people, to one or more services (e.g., a restaurantreservation service). It may be appreciated that the submittedinformation may be formatted by the backend system 550 in a mannerassociated with the one or more services. The backend system 550 mayreceive a response 542 (e.g., a confirmation, error, denial, etc.) fromthe one or more services.

FIG. 5H illustrates the receipt, by the user, of a confirmation ofperformance of the task 516, via audio 546 comprising speech and/or text544. For example, the confirmation may include details about the task516, such as location, time, cost and/or a confirmation code. Theconfirmation may be modified and/or customized based upon the firstpersonality 528 selected in FIG. 5D.

FIG. 5I illustrates an exemplary system of components of the digitalassistant of the device 500 that may be used to perform one or more ofthe actions described herein. For example, a natural languageunderstanding component 548 may receive audio comprising user speechreceived from the microphone 506 and may convert the user speech intotext (e.g., using speech recognition). A dialogue manager 551 maydetermine a task associated with the text and/or one or more sentenceswith which to respond to the user speech. An agent manager 552 maydetermine an agent 556 of a plurality of agents (e.g., 554, 556, 558,etc.) for performing the task (e.g., making a reservation). A naturallanguage generation component 564 may select a personality profile froma personality profiles component 560 based upon a user profile of theuser identified in a user profiles component 562. The natural languagegeneration component 564 may use the personality profile to customizethe one or more sentences determined by the dialogue manager 551, andmay output audio comprising speech of the customized one or moresentences via the speaker 508.

It may be appreciated that the disclosed subject matter may assist auser in performing various tasks including but not limited to thereservation of a hotel, the reservation of a flight, the reservation ofa rental car, the reservation of a restaurant, various travelarrangements, the selection of a gift (e.g., for a relative, significantother, etc.), the ordering of one or more subcomponents (e.g.,groceries) needed to make a component (e.g., a meal) and/or investing(e.g., in a market). It may be appreciated that each contemplated taskcould be associated with one or more different and/or same sentences.For example, while reservation of a hotel may be associated withsentences inquiring about a time, location, room preferences and/ornumber of occupants, investing may be associated with sentencesinquiring about a level of acceptable risk, a market preference, etc.Embodiments are also contemplated where at least some of the disclosedsubject matter may be used to assist the user in various informational,educational and/or instructional applications, such as a guidebook for alocation (e.g., a zoo, museum, etc.), learning to cook, learning alanguage (e.g., German, C++, etc.) and/or learning a subject (e.g.,electromagnetics).

In some examples, at least some of the disclosed subject matter may beimplemented on a client (e.g., a device of a user), and in someexamples, at least some of the disclosed subject matter may beimplemented on a server (e.g., hosting a service accessible via anetwork, such as the Internet).

FIG. 6 is an illustration of a scenario 600 involving an examplenon-transitory machine readable medium 602. The non-transitory machinereadable medium 602 may comprise processor-executable instructions 612that when executed by a processor 616 cause performance (e.g., by theprocessor 616) of at least some of the provisions herein. Thenon-transitory machine readable medium 602 may comprise a memorysemiconductor (e.g., a semiconductor utilizing static random accessmemory (SRAM), dynamic random access memory (DRAM), and/or synchronousdynamic random access memory (SDRAM) technologies), a platter of a harddisk drive, a flash memory device, or a magnetic or optical disc (suchas a compact disc (CD), digital versatile disc (DVD), or floppy disk).The example non-transitory machine readable medium 602 storescomputer-readable data 604 that, when subjected to reading 606 by areader 610 of a device 608 (e.g., a read head of a hard disk drive, or aread operation invoked on a solid-state storage device), express theprocessor-executable instructions 612. In some embodiments, theprocessor-executable instructions 612, when executed, cause performanceand/or implementation of an embodiment 614, such as at least some of theexample method 400 of FIG. 4, for example, and/or at least some of theexample system 501 of FIGS. 5A-5I, for example.

3. Usage of Terms

As used in this application, “component,” “module,” “system”,“interface”, and/or the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution. For example, a componentmay be, but is not limited to being, a process running on a processor, aprocessor, an object, an executable, a thread of execution, a program,and/or a computer. By way of illustration, both an application runningon a controller and the controller can be a component. One or morecomponents may reside within a process and/or thread of execution and acomponent may be localized on one computer and/or distributed betweentwo or more computers.

Unless specified otherwise, “first,” “second,” and/or the like are notintended to imply a temporal aspect, a spatial aspect, an ordering, etc.Rather, such terms are merely used as identifiers, names, etc. forfeatures, elements, items, etc. For example, a first object and a secondobject generally correspond to object A and object B or two different ortwo identical objects or the same object.

Moreover, “example” is used herein to mean serving as an instance,illustration, etc., and not necessarily as advantageous. As used herein,“or” is intended to mean an inclusive “or” rather than an exclusive“or”. In addition, “a” and “an” as used in this application aregenerally be construed to mean “one or more” unless specified otherwiseor clear from context to be directed to a singular form. Also, at leastone of A and B and/or the like generally means A or B or both A and B.Furthermore, to the extent that “includes”, “having”, “has”, “with”,and/or variants thereof are used in either the detailed description orthe claims, such terms are intended to be inclusive in a manner similarto the term “comprising”.

Although the subject matter has been described in language specific tostructural features and/or methodological acts, it is to be understoodthat the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing at least some of the claims.

Furthermore, the claimed subject matter may be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement the disclosedsubject matter. The term “article of manufacture” as used herein isintended to encompass a computer program accessible from anycomputer-readable device, carrier, or media. Of course, manymodifications may be made to this configuration without departing fromthe scope or spirit of the claimed subject matter.

Various operations of embodiments are provided herein. In an embodiment,one or more of the operations described may constitute computer readableinstructions stored on one or more computer and/or machine readablemedia, which if executed will cause the operations to be performed. Theorder in which some or all of the operations are described should not beconstrued as to imply that these operations are necessarily orderdependent. Alternative ordering will be appreciated by one skilled inthe art having the benefit of this description. Further, it will beunderstood that not all operations are necessarily present in eachembodiment provided herein. Also, it will be understood that not alloperations are necessary in some embodiments.

Also, although the disclosure has been shown and described with respectto one or more implementations, equivalent alterations and modificationswill occur to others skilled in the art based upon a reading andunderstanding of this specification and the annexed drawings. Thedisclosure includes all such modifications and alterations and islimited only by the scope of the following claims. In particular regardto the various functions performed by the above described components(e.g., elements, resources, etc.), the terms used to describe suchcomponents are intended to correspond, unless otherwise indicated, toany component which performs the specified function of the describedcomponent (e.g., that is functionally equivalent), even though notstructurally equivalent to the disclosed structure. In addition, while aparticular feature of the disclosure may have been disclosed withrespect to only one of several implementations, such feature may becombined with one or more other features of the other implementations asmay be desired and advantageous for any given or particular application.

What is claimed is:
 1. A method for dynamically selecting a personalityfor a digital assistant, comprising: receiving audio associated with aconversation with a digital assistant; using speech recognition toconvert the audio into a request comprising text; determining a taskbased upon the request; determining one or more sentences associatedwith the task; determining a context of the conversation based upon therequest and a user profile of a user; calculating a first degree ofrelevance of a first personality, of a plurality of personalities, tothe context of the conversation, wherein the first personalitycorresponds to a voice of a first person and the plurality ofpersonalities corresponds to voices of a plurality of people;calculating a second degree of relevance of a second personality, of theplurality of personalities, to the context of the conversation; inresponse to determining that the first degree of relevance is greaterthan the second degree of relevance, selecting the first personalityfrom the plurality of personalities; generating audio of the one or moresentences with the voice of the first person using the firstpersonality; and presenting the audio of the one or more sentences withthe voice of the first person as part of the conversation, via aspeaker, to the user.
 2. The method of claim 1, wherein the one or moresentences comprise one or more questions associated with informationrequired to perform the task.
 3. The method of claim 1, comprising:after the presenting the audio of the one or more sentences, receivingsecond audio, from the user via a microphone, associated with theconversation with the digital assistant; using speech recognition toconvert the second audio into a second request comprising text; anddetermining a second task based upon the second request.
 4. The methodof claim 1, wherein the second personality corresponds to a voice of asecond person.
 5. The method of claim 3, comprising: determining one ormore second sentences associated with the second task; determining asecond context of the conversation based upon the second request and theuser profile of the user; selecting the second personality, for thedigital assistant, from the plurality of personalities based upon thesecond context of the conversation; and generating audio of the one ormore second sentences using the second personality.
 6. The method ofclaim 5, comprising: presenting the audio of the one or more secondsentences as part of the conversation, via the speaker, to the user. 7.The method of claim 1, comprising: selecting a first agent from aplurality of agents stored in a database based upon the task.
 8. Themethod of claim 7, comprising: providing instructions to perform thetask via the first agent.
 9. The method of claim 8, comprising:receiving confirmation that the task has been performed via the firstagent.
 10. The method of claim 9, comprising: presenting audioindicative of the confirmation as part of the conversation, via thespeaker, to the user.
 11. The method of claim 1, wherein: the audioassociated with the conversation is received from a user via amicrophone.
 12. The method of claim 1, wherein: the generating audio isperformed in response to determining that the user prefers that theconversation be continued in an audio format of a plurality of formatsof communication stored in a database than in one or more other formatsof the plurality of formats of communication.
 13. The method of claim 1,wherein: the generating audio is performed in response to determiningthat the user prefers that the conversation be continued in an audioformat of a plurality of formats of communication stored in a databasethan in a written format.
 14. The method of claim 1, comprising: afterthe presenting the audio of the one or more sentences, receivingfeedback associated with the conversation; and lower the firstpersonality in a ranking of personalities for the user based upon thefeedback.
 15. A computing device comprising: a processor; and memorycomprising processor-executable instructions that when executed by theprocessor cause performance of operations, the operations comprising:receiving a request, from a user, associated with a conversation with adigital assistant; determining a task based upon the request;determining one or more sentences associated with the task; determininga context of the conversation based upon the request and a user profileof the user; selecting a first personality, for the digital assistant,from a plurality of personalities stored in a database based upon thecontext of the conversation, wherein each personality of the pluralityof personalities is stored in the database in association with one ormore topics, wherein the selecting the first personality is based upon adetermination that at least one of the context of the conversation orthe task is associated with a first topic in association with which thefirst personality is stored in the database; generating output of theone or more sentences using the first personality; and presenting theoutput of the one or more sentences as part of the conversation to theuser.
 16. The computing device of claim 15, wherein: the outputcomprises at least one of audio of the one or more sentences, text ofthe one or more sentences or video of the one or more sentences.
 17. Anon-transitory machine readable medium having stored thereonprocessor-executable instructions that when executed cause performanceof operations, the operations comprising: receiving a request, from auser, associated with a conversation with a digital assistant;determining a task based upon the request; determining one or moresentences associated with the task; determining a context of theconversation based upon the request and a user profile of the user;calculating a first degree of relevance of a first personality, of aplurality of personalities stored in a database, to the context of theconversation; calculating a second degree of relevance of a secondpersonality, of the plurality of personalities, to the context of theconversation; in response to determining that the first degree ofrelevance is greater than the second degree of relevance, selecting thefirst personality, for the digital assistant, from the plurality ofpersonalities; generating output of the one or more sentences using thefirst personality; and presenting the output of the one or moresentences as part of the conversation to the user.
 18. Thenon-transitory machine readable medium of claim 17, wherein: the outputcomprises audio of the one or more sentences.
 19. The non-transitorymachine readable medium of claim 17, wherein: the output comprises textof the one or more sentences.
 20. The non-transitory machine readablemedium of claim 17, wherein: the output comprises video of the one ormore sentences.